Augmented reality wireless planning and troubleshooting

ABSTRACT

The present technology includes calculating the 3-D RF propagation pattern in a space for at least one Wi-Fi access point and displaying a visualization of the RF propagation pattern in augmented reality (AR). The augmented reality view of the space can be created by capturing at least one image of the space and displaying at least one image of the space on a display with the visualization of the Wi-Fi access point RF propagation pattern on the display overlaid at least one image of the space. The disclosed technology further can calculate the RF propagation properties and render a visualization of the RF propagation patterns in a 3D space by utilizing hardware on a user device. The AR display is useful in visualizing, in-person aspects of a Wi-Fi network and coverage, and can be used in troubleshooting, maintenance, and simulations of equipment variations.

CROSS-REFERENCE TO RELATED APPLICATION

The application is a Continuation of, and claims priority to, U.S.patent application Ser. No. 17/390,692 entitled AUGMENTED REALITYWIRELESS PLANNING AND TROUBLESHOOTING, filed on Jul. 30, 2021, thecontents of which are herein incorporated by reference in its entirety.

TECHNICAL FIELD

The present technology pertains to a W-Fi visualization tool and morespecifically pertains to a Wi-Fi visualization tool that permitsvisualization of Wi-Fi in augmented reality.

BACKGROUND

Wi-Fi planning in an enterprise environment can be difficult due to theparticularities of a particular floor plan, the number of access pointsrequired to cover a floor plan, and the distribution of user devicesthroughout the day, among other challenges. Tools exist to simulateWi-Fi coverage, but these tools are approximations that are not accurateenough to plan and manage the network with sufficient predictability. Infact, many such tools rely on technicians to walk a floor afterdeployment of a network to identify areas in which Wi-Fi planning toolsare inaccurate.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary embodiments of the disclosure and are not,therefore, to be considered to be limiting of its scope, the principlesherein are described and explained with additional specificity anddetail through the use of the accompanying drawings in which:

FIG. 1 illustrates an example visualization system for presenting awireless signal propagation in 3-D according to some aspects of thedisclosed technology.

FIG. 2 illustrates an example network architecture of a visualizationsystem for presenting a wireless signal propagation in 3-D according tosome aspects of the disclosed technology.

FIG. 3 illustrates an example network architecture diagram of avisualization system for presenting a wireless signal propagation in 3-Daccording to some aspects of the disclosed technology.

FIG. 4 illustrates an example control menu for a 3-D visualizationsystem according to some aspects of the disclosed technology.

FIG. 5 illustrates an example 3-D visualization of a wireless signalpropagation according to some aspects of the disclosed technology.

FIG. 6A is a flowchart of an example method for visualizing a W-Fiaccess point 3-D RF propagation pattern in Augmented Reality (AR)according to some aspects of the disclosed technology.

FIG. 6B is a flowchart of an example method for determining an RF signalstrength at points distributed in a 3-D space according to some aspectsof the disclosed technology.

FIG. 6C is a flowchart of an example method for updating a building planfrom identified differences between a building plan and reality ascaptured and detected by a user device according to some aspects of thedisclosed technology.

FIG. 7 illustrates example AR markers for use in locating a user devicein a floor plan according to some aspects of the disclosed technology.

FIG. 8 illustrates an example access point having an indicator for usein determining an orientation of the access point according to someaspects of the disclosed technology.

FIG. 9A illustrates an example augmented reality (AR) visualizationshowing an RF signal attribute as a point cloud according to someaspects of the disclosed technology.

FIG. 9B illustrates an example augmented reality (AR) visualizationshowing an RF signal attribute as an iso-surface view according to someaspects of the disclosed technology.

FIGS. 10A, 10B, and 10C illustrate an example augmented reality (AR)embodiment showing an AR visualization as a user moves with a userdevice in an environment according to some aspects of the disclosedtechnology.

FIG. 11 illustrates an example user interface within an augmentedreality (AR) visualization according to some aspects of the disclosedtechnology.

FIG. 12 illustrates an example augmented reality (AR) visualization withan associated menu of options and information according to some aspectsof the disclosed technology.

FIG. 13 shows an example of a system for implementing certain aspects ofthe present technology.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Various embodiments of the disclosure are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the disclosure.

Overview

Disclosed are systems, apparatuses, methods, computer-readable medium,and circuits for visualizing a W-Fi access point 3-D RF propagationpattern in Augmented Reality (AR). According to at least one example,the present technology includes calculating the 3-D RF propagationpattern in a space for at least one Wi-Fi access point based on a RFpropagation model for the Wi-Fi access point. The location andorientation of a user device relative to at least one Wi-Fi access pointin the space can be determined. The present technology can be used topresent a visualization of the Wi-Fi access point RF propagation patternoverlaid a first-person perspective view of the space based on thelocation and the orientation of the user device relative to at least oneWi-Fi access point.

In some embodiments, the first-person perspective view of the space isan augmented reality view of the space, which can be created bycapturing at least one image of the space and displaying at least oneimage of the space on a display. The present technology can present thevisualization of the Wi-Fi access point RF propagation pattern on thedisplay overlaid at least one image of the space.

In some embodiments, representing the visualization of the Wi-Fi accesspoint propagation can be in a first style at a first location of theuser device, and a second style at a second location of the user device.

EXAMPLE EMBODIMENTS

Additional features and advantages of the disclosure will be set forthin the description which follows, and in part will be obvious from thedescription, or can be learned by practice of the herein disclosedprinciples. The features and advantages of the disclosure can berealized and obtained by means of the instruments and combinationsparticularly pointed out in the appended claims. These and otherfeatures of the disclosure will become more fully apparent from thefollowing description and appended claims or can be learned by thepractice of the principles set forth herein.

The disclosed technology addresses the need in the art for a Wi-Fivisualization tool that is accurate in 3-D. Rather than merelycalculating an RF propagation pattern at a single standard height andassuming that the RF propagation pattern extends uniformly at allheights, the present technology calculates RF propagation properties andmany points in space including all three (X, Y, and Z) dimensions.

The disclosed technology further can calculate the RF propagationproperties and render a visualization of the RF propagation patterns ina 3D space by utilizing hardware on a user device.

Collectively these improvements further enable RF propagationvisualizations to be overlaid video captured by a user device to providean augmented reality (AR) display of an RF environment created by Wi-Fiaccess points. The AR display is useful in visualizing, in-personaspects of a Wi-Fi network and coverage, and can be used introubleshooting, maintenance, and simulations of equipment variations.

FIG. 1 illustrates an example 3-D signal propagation visualizationsystem 100 for presenting a wireless signal propagation in 3-D accordingto some aspects of the disclosed technology. As shown in FIG. 1 , the3-D signal propagation visualization system 100 can include one or moreservices primarily responsible for examining and analyzing signals froma plurality of access points (APs) 102A, 102B, 102C, . . .(collectively, 102), determining a signal propagation pattern for theAPs 102 based on a signal propagation model, and providing a 3-Dvisualization of the signal propagation pattern including analysis,troubleshooting, simulations, or optimizations of the signal propagationpattern.

The 3-D signal propagation visualization system 100 can include an APdatabase 104 that includes information about the plurality of APs 102,which are configured to transmit wireless communication signals. In someaspects, the information about the plurality of APs 102 can include, butis not limited to a location of APs 102 and their orientation (e.g.,azimuth and elevation angles), a model number, a signal strength,end-of-life data, an antenna type, a channel, a frequency (band), ornetwork information of which the APs 102 belong.

The 3-D signal propagation visualization system 100 can include an APmodel service 106 that is a collection of signal propagation models fordifferent types of AP antennae 102. In some examples, the signalpropagation model includes a description of the signal propagationpattern based on the information associated with the AP antennae 102.For example, such information can be provided by the AP database 104 orrelated to parameters derived from various configuration attributes andmeasurements such as transmission power (txPower), signal-to-noise ratio(SNR), Key Performance Indicator (KPI) values, or Received SignalStrength Indication (RSSI) values.

The 3-D signal propagation visualization system 100 can include avisualization service 108 configured to perform 3-D modeling, i.e.,display a 3-D visualization of the signal propagation pattern based onthe signal propagation model. In some examples, the visualizationservice 108 can display the 3-D visualization of the signal propagationin the form of a heatmap, which uses color-coding to represent differentvalues of the signal strength. In some instances, the visualizationservice 108 can generate a time-based (temporal) visualization wherechanges in the signal propagation pattern over time can be presented inthe 3-D visualization.

The 3-D signal propagation visualization system 100 can also include aray tracing service 110 configured to perform ray tracing from aparticular AP. In some examples, the ray-tracing service 110 can computeattenuation based on the line-of-sight from a particular AP to a certainvertex in space. For example, ray tracing can be used to visualize thesignal propagation by tracing paths of electromagnetic waves andsimulating the way that the waves interact with any objects it may hit.If a straight line is drawn from a particular AP and does not hitanything in the space, then the signal propagation model works in astraightforward manner. On the other hand, if there is an obstacle(e.g., a wall, shelving, ceiling, etc.) along the path, the signalpropagation pattern can be broken into multiple segments since thesignal propagation pattern can change depending on the properties of theobstacle that the pattern has to pass through.

The 3-D signal propagation visualization system 100 can include atelemetry service 112 configured to collect and record data from theplurality of APs 102 or sensors on the floor pertaining to the APs 102in space. In some examples, the telemetry data can be used to updateinformation about a particular AP (e.g., model, antenna type, etc.) orfeed into the visualization service 108 to provide an optimized 3-Dvisualization instead of relying on a predicted model. In someinstances, the telemetry service 112 can utilize the telemetry data tovalidate a certain predicted model.

The 3-D signal propagation visualization system 100 can also include ananalysis service 114 that is configured to analyze data associated withthe wireless coverage such as SNR measurements, latency measurements, anumber of client devices at each of the APs, KPI values, txPowermeasurements, or RSSI measurements. In some instances, the analysisservice 114 can further perform analysis pertaining to data associatedwith one or more errors or constraints of the APs 102 that can impactthe wireless coverage.

The 3-D signal propagation visualization system 100 can include atroubleshooting service 116 configured to perform various types oftroubleshooting by isolating and root-causing issues or errors relatingto the network performance and signal propagation pattern based on theAPs 102 and providing suggestions to resolve such issues or errors. Insome examples, the troubleshooting service 116 can identify both causeand consequences of the issues, for example, obstructions in the line ofsight, a level of signal coverage, a number of client devices connectedto APs, co-channel interference, or stickiness to APs.

The 3-D signal propagation visualization system 100 can include anoptimization service 118 configured to provide a 3-D visualization ofthe optimized signal propagation pattern that provides betteroperational signal coverage and lower interference. In some examples,the optimization service 118 can provide an upgrade option for the APsor configuration settings to achieve improved network performance. Insome instances, the optimization service 118 can provide the optimized3-D visualization that illustrates dynamic changes as conditions in thenetwork change. In some examples, the optimization service 118 canpropose different optimized layouts by radio spectrum (RF) or deploymentof the APs for a given space.

The 3-D signal propagation visualization system 100 can also include asimulation service 120 configured to simulate various scenarios relatingto deployment of APs, potential network failures, estimated RF leakage,or alternative network configurations. In some instances, the simulationservice 120 can provide a simulated 3-D visualization of the variousproposed layouts provided by the optimization service 118.

In some examples, the simulation service 120 can provide a simulated 3-Dvisualization illustrating the impact of an alternative deployment ofAPs, for example, how the signal propagation pattern is impacted bydeploying a new or upgraded AP at different locations on the floor.Also, the simulation service 120 can simulate a 3-D visualization basedon the impact of an upgrade or different AP upgrade strategies prior tothe actual update to observe and compare the wireless coverage.

Furthermore, a type of materials of obstructions in the space cansignificantly impact the signal propagation pattern. The simulationservice 120 can provide a simulated visualization of the signalpropagation pattern depending on the type of materials of obstacles suchas walls or shelving, or what is stored on shelving (e.g., liquid,metal, non-metal, etc.).

Additionally, the simulation service 120 can provide a simulated 3-Dvisualization illustrating potential network failures. For example, thesimulation service 120 can help define coverage zones to avoid coverageblackout zones in common.

The 3-D signal propagation visualization system 100 can also include auser location service 122 configured to identify a location of a user(e.g., client device) and obtain data associated with the user/clientdevice to determine the signal propagation pattern. For example, aclient density can significantly affect the wireless network coverage.

In some examples, the user location identified by the user locationservice 122 can be combined with an AP coverage so that the 3-Dvisualization can include the impact of the client device such as anoperating system of client devices, client device density, or any RFinterference due to the presence of RF-emitting device (e.g., mobilephones, cordless phones, wireless security cameras, etc.).

In some examples, the user location service 122 can help to optimize thelatency and the signal propagation pattern by identifying the locationof client devices and the type of services that the client devices areperforming. For example, too many client devices performing VoIP callson the same AP can worsen the network performance and cause a bad callquality due to latencies. The 3-D visualization of the signalpropagation pattern can include the user location provided by the userlocation service 122 to illustrate such impact of the client devices onthe wireless network coverage.

The 3-D signal propagation visualization system 100 can also include abuilding plan design service 124 configured to allow a user to managethe settings of the building plan or the floor plan of the space (e.g.,layout, objects, viewpoint, etc.).

The 3-D signal propagation visualization system 100 can include abuilding plan import service 126 configured to import a building plan ora floor plan. The building plan or the floor plan can be in any suitableformat, for example, a Building Information Modeling (BIM) file or aComputer-Aided Design (CAD) file. In some examples, the building planimport service 126 can import the building plan or the floor plan thatcontains a technical drawing, blueprint, schematic, or 3-D rendering ofthe floor that is to be visualized in 3-D.

In some instances, the signal propagation pattern can be overlaid overthe building plan or the floor plan provided by the building plan importservice 126. Depending on the type of the imported file for the buildingplan, details of the building or the floor such as a type of materialsof the obstacles (e.g., a wall, etc.) or location of APs or sensors canfurther be included in the building plan.

The 3-D signal propagation visualization system 100 can also include abuilding plan layout service 128 configured to store the building planlayout and support the 3-D visualization of the building plan layout. Insome examples, the building plan layout service 128 can perform thefunction of a management and control platform for managing, monitoring,and storing data associated with the visualization based on the buildingplan.

The 3-D signal propagation visualization system 100 can also include auser interface service 130 configured to allow a user to manage andcontrol settings of the visualization or network configurations tooptimize the 3-D visualization. For example, the settings can include aviewpoint (e.g., a first-person perspective, an orbit view, or a bird'seye view), layout, parameters (e.g., txPower, SNR measurements, KPIvalues, RSSI values, etc.), or visualization options. Also, the examplesof network configurations can include but are not limited to elevationor azimuth angle of APs, deployment of APs, band and a type of networkor APs.

In some instances, the user interface service 130 can provideinformation to or receive feedback from the user via a communicationservice 132 as further described below. In some examples, the user maybe asked to evaluate and manage various suggestions proposed by thetroubleshooting service 116 or the optimization service 118.

The 3-D signal propagation visualization system 100 can also include acommunication service 132 configured to transmit and receive informationwirelessly over a network. In some examples, the communication service132 can send and receive communications from/to a building plan system(not shown) that may provide building plan updates. In some instances,the communication service 132 can transmit and receive data from/to auser for analyzing, troubleshooting, simulating, or optimizing the 3-Dvisualization of the signal propagation pattern.

FIG. 2 illustrates an example network architecture 140 for the 3-Dsignal propagation visualization system 100 illustrated in FIG. 1according to some aspects of the disclosed technology. The networkarchitecture 140 comprises a wireless network 150, sales tools 160, anetwork controller 170, a Wi-Fi 3-D analyzer 180, and a user 190. Insome embodiments, Wi-Fi 3-D analyzer 180 executes on a client device andtakes advantage of hardware acceleration capabilities from a graphicsprocessor, but Wi-Fi 3-D analyzer 180 can operate in other environmentssuch as a server or on a device with only general processingcapabilities. Even though the network controller 170 and Wi-Fi 3-Danalyzer 180 are illustrated as separate components in FIG. 2 , in someexamples, they can be a single device (i.e., the Wi-Fi 3-D analyzer 180is run on the network controller 70 itself).

The wireless network 150 comprises APs 102 illustrated in FIG. 1 ,sensor(s), and user devices. The network controller 170 can include APdatabase 104, AP model service 106, telemetry service 112, user locationservice 122, building plan design service 124, building plan importservice 126, and building plan layout service 128, all of which areillustrated in FIG. 1 . The Wi-Fi 3-D analyzer 180 can includevisualization service 108, analysis service 114, troubleshooting service116, optimizations service 118, simulation service 120, and userinterface service 130, all of which are also illustrated in FIG. 1 .

The wireless network 150 can transmit sensor data 152, assurance data154, and/or telemetry data 156 to the network controller 170. Thenetwork controller 170 can store such received data and can provide userinterfaces and APIs for receiving network configurations and updates.Network configurations can be used to provision 158 various devices inwireless network 150. Also, the network controller 170 can transmit livedata 172, 3-D maps 174 (e.g., 3-D building plans or floor plans), and/orhardware models 176 to the Wi-Fi 3-D analyzer. While not shown in FIG. 2, alternatively, live data 172, 3-D maps 174, and/or hardware models 176can be exported to cloud instead of a local PC or GPU and provide user190 with insights 186.

The Wi-Fi 3-D analyzer 180 can use the 3-D maps 174 and hardware models176 to generate predictions or simulations of wireless signalpropagation and their correlation with the live data 172. Based on thedata received from the network controller 170, the Wi-Fi 3-D analyzer180 can provide wireless 3-D rendering 182, simulation 184, and/orinsights 188 to the user 190. For example, the user can be provided withthe wireless 3-D rendering 182 of the wireless signal coverage (e.g., RFcoverage) and options to run simulations 184 for what-if scenarios, andinsights 186 including suggestions for improving the network performanceassociated with the wireless signal coverage. Based on what is providedby the Wi-Fi 3-D analyzer 180, the user 190 can take action 188accordingly, for example, modifying a network configuration to improvethe network performance. Wi-Fi 3-D analyzer 180 can forward any updatesto the network configuration for provisioning 178 to the networkcontroller 170.

Furthermore, the sales tools 160 can provide a product upgrademanagement based on the communication flow between the sales tools 160,the network controller 170, and the Wi-Fi 3-D analyzer 180. The salestools 160 can transmit new products and lifecycle data 162 to thenetwork controller 170. Then the network controller 170 forwards the newproducts and lifecycle data 164 to the Wi-Fi 3-D analyzer 180. The newproducts and lifecycle data 162 and 164 can include new productavailability for sale or end-of-life dates for AP products.

Based on the new products and lifecycle data 164, the Wi-Fi 3-D analyzer180 can provide upgrade proposals 166, which can include simulation 184and insights 186 on product upgrade, to the user 190. Also, in responseto the upgrade proposals, the user 190 can place a new product order 168by utilizing the sales tools 160. For example, the new products andlifecycle data 162 can include end-of-life data associated with aparticular AP so that an upgrade or replacement of a new AP can berecommended based on the end-of-life data prior to the expiry of the AP.Also, the user 190 can place an order for a new AP with the sales tools160.

FIG. 3 illustrates an example network architecture diagram for awireless network 150, a network controller 170, and a Wi-Fi 3-D analyzer180 according to some aspects of the disclosed technology. The wirelessnetwork 150, also illustrated in FIG. 2 , comprises APs 102 and sensors103 and client devices 105.

The wireless network 150 can transmit telemetry feedback (for example,telemetry data 156 illustrated in FIG. 2 ) to the network controller170. For example, each AP 102 transmits beacons to the sensor 103whereby a sensor report can be generated. Also, the APs 102 communicatewith each other via inter-AP Neighbor Discovery Protocol (NDP) togenerate neighbor reports. Furthermore, client device 105 measuresbeacons and returns a report with stored beacon information (e.g.,802.11k beacon reports). Based on the neighbor reports, 802.11k beaconreports, and sensor reports, the wireless network 150 provides telemetryfeedback to the network controller 170. The telemetry feedback caninclude information about a distance and azimuth angle between a pair ofAPs or an AP and a sensor and walls or any obstructions between the pairon a building plan or a floor plan. Also, network controller 170includes location information of client devices based on RSSI location,which is received from the wireless network 150.

Based on the data provided by the wireless network 150, the networkcontroller 170 and the Wi-Fi 3-D analyzer 180 can determine a predictiveRSSI model and visualize the predicted RSSI at all 3-D locations.

FIG. 4 illustrates an example menu 200 including a list of variousparameters that can be adjusted for the 3-D visualization of thewireless signal propagation.

The menu 200 provides an option for key performance indicator (KPI)heatmap metrics 202, for example, none, RSSI, SNR, or Interference.Depending on the selected heatmap metrics, the 3-D visualization of thewireless signal propagation can be presented based on RSSI values, SNRmeasurements, or interference measurements. RSSI values are a predictedor measured power level at a point in space of an RF transmitted from anAP. SNR measurements are based on the amplitude of signal and noiselevel. Interference measurements or predictions are based on the powerof the interfering signals.

The menu 200 also provides an option for heatmap type 204, for example,point cloud, isosurface, or scanner. A point cloud heatmap provides the3-D visualization of the wireless signal propagation as a collection ofcolor-coded points where a color variation corresponds to a degree ofsignal strength. An isosurface heatmap displays the 3-D visualization ofthe wireless signal propagation with isosurfaces (e.g., contour lines orsurfaces) where each isosurface represents points of equal values in a3-D space. A scanner provides the 3-D visualization of the wirelesssignal propagation with color-coded bands where the color of the bandscorrespond to a degree of signal strength. Also, the scanner allows auser to manipulate a height in the 3-D space, for example, via a heightmanipulation bar under a cut height 208 so that the wireless signalpropagation pattern can be scanned through the 3-D space, for example,from a ground to a ceiling and visualized at varying heights.

Furthermore, a heatmap opacity 206 can be adjusted, for example, in ascale of 0 (i.e., non-transparent) to 100 (i.e., fully transparent) toadjust the transparency of the 3-D visualization.

Also, cut height (ft) 208 can be adjusted, for example, in a scale of 0to 10. A user can select a particular height where the 3-D visualizationis desired. Or, with a play button and a pause button, the 3-Dvisualization of the wireless signal propagation can be simulated atcontinuously varying heights from 0 ft to 10 ft.

The menu 200 also provides an option where a visualization of telemetrydata 210 can be switched on and off. Also, telemetry threshold 212 canbe adjusted, for example, in a scale of −100 to −35.

Furthermore, the menu 200 provides an option for a RF Model selection214. For example, a drop-down list provides various options for the RFmodel such as cubes and walled offices, drywall offices, or open space.

While not shown in FIG. 4 , menu 200 can include different oralternative options. For example, menu 200 could include an option forclipping a 3-D floor plan to take cross-sections of the floor plan toallow clear visualization of an area of interest. Menu 200 could includean adjustable noise floor to be used in calculating a signal-to-noiseratio (SNR). Menu 200 could include an option to change the model of APbeing visualized to permit comparisons between various hardware options.Menu 200 could include an option to adjust the frequency band from 2.4GHz to 5 GHz to visualize attributes associated with RF propagation atthose frequencies. The 2.4 GHz band typically provides a greaterdistance of coverage, while the 5 GHz band typically provides fastercommunication speeds. Menu 200 can include antennae options that mightpermit visualizations using directional antennas or omnidirectionalantennas. Menu 200 could provide options for adjusting transmissionpower of an antenna, or a channel. Menu 200 could also provide varioussliders for visualizing animations such as a time scale. Accordingly,the menu can provide many options that can vary depending on the type ofvisualization being presented.

FIG. 5 illustrates an example 3-D visualization 300 of Wi-Fi AP RFsignal propagation. In the 3-D visualization 300, the 3-D visualizationof a building plan (e.g., floor plan) is overlaid with RF propagationpatterns. As shown in FIG. 5 , the 3-D visualization 300 illustrates theRF signal propagation patterns as a collection of zones 302 where eachzone represents a service area covered by each AP 102 (e.g., AP 102illustrated in FIG. 1 ). Each zone is in the shape of a dome toillustrate a signal strength in the service area in 3-D instead of asimple flat layer in 2-D. Furthermore, the color and size of the domescorrespond to a degree of signal strength from the AP in the servicearea. In FIG. 5 color is distinguished by domes that outlined in solidor dashed lines. The dome shape acknowledges that the RF propagationfrom an AP is not uniform at all heights of a floor plan. The dome shapeis determined from calculating the RF propagation attribute at manypoints in X, Y, and Z space.

While it is difficult to see in FIG. 5 domes representing RF signalpropagation and overlap one another. This is more easily viewed on acomputer graphical user interface that can use translucent shading toindicate overlapping regions.

Even though the 3-D visualization 300 of Wi-Fi AP RF signal propagationin FIG. 5 uses a color-coded dome model, the 3-D visualization of the RFsignal propagation according to the present disclosure can be providedin the form of a point cloud model, a heat map, or a contour map toillustrate the degree of signal strength in the 3-D space.

FIG. 6A illustrates an example method for visualizing a W-Fi accesspoint 3-D radio frequency (RF) propagation pattern in Augmented Reality(AR). Although the example method depicts a particular sequence ofoperations, the sequence may be altered without departing from the scopeof the present disclosure. For example, some of the operations depictedmay be performed in parallel or in a different sequence that does notmaterially affect the function of the method. In other examples,different components of an example device or system that implements themethod may perform functions at substantially the same time or in aspecific sequence.

According to some embodiments, the method includes calculating the 3-DRF propagation pattern in a space for at least one Wi-Fi access pointbased on a RF propagation model for the Wi-Fi access point at block 402.For example, the visualization service 108 illustrated in FIG. 1 maycalculate the 3-D RF propagation pattern in a space for at least oneWi-Fi access point based on a RF propagation model for the Wi-Fi accesspoint, the antenna pattern of the Wi-Fi access point, the configurationof the Wi-Fi access point (txPower, azimuth, elevation, band andchannel) and the geometry of a space as defined in a building plan.

An example method for calculating the 3-D RF propagation pattern isillustrated in FIG. 6B. The method includes projecting a plurality ofray paths in a plurality of directions in a 3-D space at block 432. Forexample, the ray tracing service 110 illustrated in FIG. 1 may project aplurality of ray paths in a plurality of directions in a 3-D space. Insome embodiments, the ray paths originate from the Wi-Fi access pointand emanate in a variety of X, Y, and Z planes.

The method includes determining whether the ray paths interface with abuilding material defined in a building plan at block 434. For example,the ray tracing service 110 illustrated in FIG. 1 may determine whetherthe ray paths interface with a building material defined in a buildingplan.

The method includes segmenting each ray-path of the ray-paths thatinterface with a building material the respective ray-path intocontiguous segments of substantially uniform mediums at block 436. Forexample, the ray tracing service 110 illustrated in FIG. 1 may segmentthe respective ray path into contiguous segments of substantiallyuniform mediums.

The ray-tracing service 110 can provide the segmented ray paths to an APmodel service 106. The combination of the collection of ray paths forany access point and model information from AP model service 106 can beprovided to visualization service 108.

The method includes determining a RF signal strength at points along thesegments of the ray-paths at block 438. For example, the visualizationservice 108 illustrated in FIG. 1 may determine a RF signal strength atpoints along the segments of the ray paths. The visualization service108 can use the information about the collection of ray paths for anyaccess point and a RF propagation model particular to the type of accesspoint and the parameters for the specification access point to determinethe RF signal strength at points along the segments of the ray-paths. Insome embodiments, the signal degrades along the ray path as defined bythe RF propagation model as a function of distance through the segmentand characteristics of RF propagation through the substantially uniformmediums through which the segment traverses.

In order to present a visualization in augmented reality (AR),visualization service 108 needs to receive inputs of both preciselocation and orientation information from the user device. Thisinformation is needed to coordinate an image scene captured by a userdevice 105 camera and displayed on a display of the user device 105, andthe calculated RF propagation model so that the RF information can beoverlaid the image of the scene displayed by the user device 105. Thislocation and orientation information can come from multiple sources.

According to some embodiments, the method includes determining alocation and orientation of a user device relative to at least one Wi-Fiaccess point in the space at block 404. For example, the user locationservice 122 illustrated in FIG. 1 may determine a location andorientation of a user device relative to at least one Wi-Fi access pointin the space. For this source of location and orientation information,user location service 122 can utilize information reported by userdevice 105 regarding signal strength of nearby access points to performmultilateration or other location identifying techniques that will workindoors. However such techniques are often only accurate within a rangeof several meters, and therefore this technique on its own may not beprecise enough.

Another source of location and orientation information can be from theuser device 105 if the user device 105 is capable of detecting andranging the floor plan. In such embodiments, a user device can usemachine vision techniques to estimate its distance from one or moreobjects, but these techniques are not accurate enough to identify alocation in space on their own. In another mechanism of detecting andranging, the user device 105 would need to be capable of creating apoint cloud, like a LiDAR point cloud of all surfaces in the space, andcoordinate such a point cloud with the building plan layout service 128.Unfortunately, not all devices have such a capability. Also, floor planscan change, and furniture can be added or removed which can causeproblems when coordinating a point cloud detected by the device with thefloor plan in the building plan layout service 128.

Another way of locating and orientating the user device 105 relative toat least one Wi-Fi access point in the space includes detecting at leastone indicator on the Wi-Fi access point that uniquely identifies theWi-Fi access point and/or the location of the Wi-Fi access point. Forexample, the user device 105 may detect at least one indicator or markeron the Wi-Fi access point that uniquely identifies the Wi-Fi accesspoint and/or the location and/or the orientation of the Wi-Fi accesspoint. In some embodiments, at least one indicator is a QR code,symbols, an optical pattern, a pattern of blinking lights, or theorientation and geometry of a housing of the Wi-Fi access point. Anexample of such indicators can be seen in FIG. 7 . Using this method,the user device 105 can look up information about the indicator in APdatabase 104 to learn where the AP 102 is located on the floor plan. Theuser device 105 then only needs to determine how close it is to theidentified AP 102, which can be accomplished in combination with one ofthe other sources of location information described herein. While thoseother sources such as multilateration or determining a range of anobject using machine vision might not be sufficient to identify aprecise location on their own, they can be much more precise incombination with a known marker. Additionally, once an initial locationis known, the mobile device can use other sensors such as gyroscopes andaccelerometers to track movement from the initial location.

The detection of at least one indicator at block 448, is further usefulnot only to determine a more precise location but also for determiningan orientation of the Wi-Fi access point in the space. It is importantto know the orientation of the Wi-Fi access point for several reasons.For example, when the orientation of the Wi-Fi access point is known,this can be used to determine the orientation of the user device 105 inspace as well. The known orientation of the Wi-Fi access point is areference point. In addition, it is important to know the orientation ofthe Wi-Fi access point because some Wi-Fi access points have directionalantennas. The user device 105 can identify a marker on the Wi-Fi accesspoint, look up the Wi-Fi access point based on the marker indicating theorientation of the Wi-Fi access point in AP database 104, and receiveinformation about the configuration of the Wi-Fi access point and itsantennas relative to the orientation indicated by the visible markers.An example of a marker on an access point can be seen in FIG. 8 .

Further, at least one indicator on the Wi-Fi access point is importantfor uniquely identifying the particular Wi-Fi access point. A visiblemarker can be used to identify the access point, and user device 105 cancommunicate with AP database 104 to learn an identification of the Wi-Fiaccess point, its location, and/or its orientation in the space. Asnoted above, this information is important to learn information aboutconfigurations of the access point, and orientations of the Wi-Fi accesspoint 102 and user device 105. All of this information can be providedto visualization service 108.

According to some embodiments, once a location of the user device 105 isknown, the method includes presenting a visualization of the Wi-Fiaccess point RF propagation pattern overlaid a first-person perspectiveview of the space based on the location and the orientation of the userdevice relative to the at least one Wi-Fi access point at block 406. Forexample, the visualization service 108 illustrated in FIG. 1 may presenta visualization of the Wi-Fi access point RF propagation patternoverlaid a first-person perspective view of the space based on thelocation and the orientation of the user device relative to at least oneWi-Fi access point. In some embodiments, the first-person perspectiveview of the space is an augmented reality view of the space, wherein alive image is captured and displayed by user device 105, andvisualization service 108 overlays the visualization over the liveimage. Examples of some AR visualizations are illustrated in FIG. 9A,FIG. 9B, FIG. 10 , FIG. 11 , and FIG. 12 .

In some embodiments, the visualization of the Wi-Fi access point RFpropagation pattern illustrates at least one attribute of the Wi-Fipropagation pattern, such as signal-to-noise ratio (SNR), signalstrength, interference, the channel of the access points, etc. In someembodiments, at least one Wi-Fi access is a plurality of Wi-Fi accesspoints, and the visualization of the Wi-Fi access point RF propagationpattern illustrates RF propagation patterns for the plurality of Wi-Fiaccess points. For example, the visualization can display a RFpropagation from a plurality of Wi-Fi access points which might allow auser to see coverage area overlaps or gaps, or interference between theRF propagation patterns, among other insights.

The AR visualization can also include a labeled reference iconindicating a first Wi-Fi access point in the space through which theuser device is presently communicating. For example, the visualizationservice 108 illustrated in FIG. 1 may include a reference iconindicating a first Wi-Fi access point in the space through which theuser device is presently communicating. This can be useful when the ARvisualization is displaying information about a particular Wi-Fi accesspoint that is different than the access point through which the userdevice 105 is communicating. Should the user of user device 105 want tosee information about the Wi-Fi access point to which its user device isattached, the AR visualization can provide an arrow or other indicatorto guide the user toward the access point to which their device isconnected.

In some embodiments, the AR visualization can be particularly useful tosee coverage around objects that do not appear in a building plan. Forobjects that do appear in a building plan, it is possible to simulate orvirtualize the objects in the building plan and view them by walkingthrough a virtual floor plan, but for objects that exist in real life,but are not in the floor plan the virtual or simulated environment willnot have knowledge of these objects and the will not be displayed.Accordingly, the AR visualization can be used to view Wi-Fi coveragearound objects such as desks or other furniture or other objects thatexist in the physical space that are not present on the floor plan.

Further, the method can include detecting an object that does not appearin the building plan. For example, the visualization service 108illustrated in FIG. 1 may detect the object that does not appear in thebuilding plan in the video captured by the user device 105 and can labelthe object that does not appear in the building plan when an aspect ofthe Wi-Fi access point RF propagation pattern surrounding the object isof poor quality as indicated by the aspect of the RF propagation patternbeing below a threshold. For example, the AR visualization can draw theuser's attention to objects that are not receiving quality Wi-Ficoverage. In some embodiments, the visualization service 108 can includemachine vision capabilities to recognize objects that should besurrounded by quality Wi-Fi coverage. For example, it is more importantto identify a desk that does not have quality Wi-Fi coverage, but it isnot important to identify a plant that does not have good Wi-Ficoverage. Accordingly, in some embodiments, the highlighting objectsthat do not have good Wi-Fi coverage can be limited to certain types ofobjects that the visualization service 108 is trained to recognize.

According to some embodiments, the method includes continuouslydetermining the location and orientation of the user device relative toat least one Wi-Fi access point at block 408. For example, the mobiledevice 105 illustrated in FIG. 3 may continuously determine the locationand orientation of the user device relative to at least one Wi-Fi accesspoint.

According to some embodiments, the method includes dynamically adjustingthe visualization of the Wi-Fi access point RF propagation pattern incoordination with continuously determining the location and orientationof the user device relative to at least one Wi-Fi access point at block410. For example, the visualization service 108 illustrated in FIG. 1may dynamically adjust the visualization of the Wi-Fi access point RFpropagation pattern in coordination with the continuously determinedlocation and orientation of the user device relative to at least oneWi-Fi access point.

In another example of the dynamically adjusting the visualization of theWi-Fi access point RF propagation pattern in coordination with thecontinuously determining the location and orientation of the user devicerelative to at least one Wi-Fi access at block 410, the method comprisesrepresenting the visualization of the Wi-Fi access point propagation ina first style at a first location of the user device, and representingthe visualization of the Wi-Fi access point propagation in a secondstyle at a second location of the user device For example, as the usermoves around with the user device 105, they can enter a bubblerepresenting an RF propagation pattern or leave a bubble. The bubbles or3-D areas representing the RF propagation pattern can be color-codedaccording to various attributes and as the user moves around a floorplan the RF propagation attributes might change. In one example, whenthe user is at a first location, they might be viewing the RF signalstrength of a Wi-Fi access point. The RF signal strength can berepresented showing a green surface representing a boundary within whichthe RF signal strength from the access point is greater than −65 dB. Asthe user moves further away from the access point, they might seeanother boundary in red within which the RF signal strength is greaterthan −80 dB. An example of such visualizations is illustrated at FIG. 9Aand FIG. 9B.

In addition, to update the AR visualization to correspond to movementsof the user device 105, the AR visualization can include an interactiveuser interface. According to some embodiments, the method includesreceiving a selection of the Wi-Fi access point in the visualization atblock 412. For example, the user interface service 130 illustrated inFIG. 1 may receive a selection of the Wi-Fi access point in thevisualization.

In response to receiving the selection of the Wi-Fi access point, thevisualization service 108 can present statistics and informationpertaining to the Wi-Fi access point at block 414.

In some embodiments, the visualization service 108 can present optionspertaining to additional visualizations of the Wi-Fi access point RFpropagation pattern at block 416. In response to the user interfaceservice 130 receiving a selection of one or more options pertaining toadditional visualizations of the Wi-Fi access point RF propagationpattern, the visualization service 108 can present a visualization ofthe Wi-Fi access point RF propagation pattern corresponding to theselected option at block 418. For example, a user could select an optionto show RF signal strength, or channels of access points, orinterference areas, etc.

FIG. 6C illustrates an example embodiment wherein the images captured bythe user device of objects in the building plan can be used to updatedata in the building plan file.

In some embodiments, the method comprises identifying a portion of thebuilding plan in at least one image of the space at step 452. Forexample, the visualization service 108 illustrated in FIG. 1 mayidentify a portion of the building plan in at least one image of thespace that is captured by user device 105.

Further, the method includes identifying a material that comprises theportion of the building plan at step 454. For example, the visualizationservice 108 illustrated in FIG. 1 may identify a material that comprisesthe portion of the building plan and can determine that the materialthat comprises the portion of the building plan is different than thebuilding material recording the building plan for the portion of thebuilding plan at step 456. For example, when the visualization service108 illustrated in FIG. 1 determines that the material that comprisesthe portion of the building plan is different than the building materialrecorded the building plan for the portion of the building plan, thevisualization service 108 can update the building plan with theidentified material at step 460. This can be useful when some change hasoccurred since the building plan was created. Whether differentmaterials had to be used during building or a renovation occurred, thepresent method can be used to automatically update the building planfile.

In some embodiments, the method comprises identifying a configurationchange in the building plan from at least one image of the space at step459. For example, the visualization service 108 illustrated in FIG. 1may identify a configuration change in the building plan as compared tothe recorded building plan from at least one image of the space. Forexample, the configuration change could be due to a renovation since thebuilding plan file was last updated, or maybe workstations have beenmoved or installed. When it is determined that a configuration changehas occurred, the visualization service 108 illustrated in FIG. 1 mayupdate the building plan with an updated configuration.

The updated configurations can be used by the visualization service tocalculate more accurate RF propagation patterns for the currentparameters of the floor plan.

FIG. 7 illustrates an example AR visualization captured by user device105 and presented on the display of user device 105. The visualizationincludes an image or video of a space that is part of a building plan.As illustrated in FIG. 7 , there is a plurality of AR markers 505located throughout the space. These AR markers can be recognized by userdevice 105 using machine vision techniques. Each of these markers isunique and thus user device 105 can uniquely identify a particular ARmarker and then look up the AR marker in a database to receiveinformation regarding the location of the AR marker in the buildingplan. In addition, some of their markers can be placed on Wi-Fi accesspoints and can be used to uniquely identify the access point asaddressed above. In some embodiments, the marker is a QR code, symbols,an optical pattern, a pattern of blinking lights, or the orientation andgeometry of a housing of the Wi-Fi access point. Using this method, theuser device 105 can look up information about the marker in AP database104 to learn where the AP 102 is located on the floor plan. The userdevice 105 then only needs to determine how close it is to theidentified AP 102, which can be accomplished in combination with one ofthe other sources of location information described herein. While thoseother sources such as multilateration or determining a range of anobject using machine vision might not be sufficient to identify aprecise location on their own, they can be much more precise incombination with a known marker. Additionally, once an initial locationis known, the mobile device can use other sensors such as gyroscopes andaccelerometers to track movement from the initial location.

FIG. 7 also illustrates a thumbnail floorplan 503 providing context tothe user by illustrating the current location of user device 105 in thefloor plan.

FIG. 8 illustrates an example access point 510. Access point 510 has anappended indicator 512. Indicator 512 can be used to determine aparticular orientation of the access point. As addressed above it is notenough to merely identify an access point, it is important to know theorientation of the access point and the relative orientation of the userdevice to the access point 510 in order to provide accurate RFprojections.

In some embodiments, indicator 512 can be physically appended to accesspoint 510. In some embodiments indicator, 512 can be a marker or drawingor symbol labeled on access point 510.

FIG. 9A and FIG. 9B illustrates an example AR visualization showing aportion of a floor plan captured by a camera and displayed on a displayof a mobile device 105. Mobile device 105 can recognize one or moremarkers 505 to help identify the location and orientation of mobiledevice 105 in the floor plan.

As addressed above, visualization service 108 can present avisualization overlaid the captured floor plan. As illustrated in FIG.9A, visualization service 108 can display radio frequency (RF) signalstrength overlaid the view captured by the camera of mobile device 105.The RF signal strength (or any other selected key performance indicator(KPI)) can be illustrated as a collection of points in a point cloud.Some points, such as those labeled 525, have a signal strength greaterthan a first threshold such as −65 decibels can be illustrated in onecolor whereas some points, such as those labeled 521, have a signalstrength greater than a second threshold, such as −90 decibels butgreater than −65 decibels, can be displayed in a second color.

In some embodiments, the visualization overlayed the captured floorplancan also include a user interface element 515 that is effective toadjust the signal strength thresholds corresponding to the firstthreshold and the second threshold.

FIG. 9B illustrates a similar embodiment to that illustrated in FIG. 9Aexcept that in FIG. 9A the RF signal strength is indicated as acontinuous boundary rather than a point cloud. As such in FIG. 9B aboundary of an area having a signal strength greater than the firstthreshold is illustrated in one color 530, and a boundary of an areahaving a signal strength between the second threshold and the firstthreshold can be illustrated in the second color 535. As illustrated inFIG. 9B, the boundary of the first threshold 530 is in the shape of abubble. This acknowledges that the RF propagation from an AP is notuniform at all heights of a floor plan.

FIG. 10A, FIG. 10B, and FIG. 10C all illustrate a progression ofexamples of an augmented reality (AR) embodiment. For example, in FIG.10A, user device 105 has captured an image of a table with an accesspoint sitting on it. Visualization service 108 displays a visualizationoverlaid the captured image of a color-coded RF propagation patternwherein a first color boundary 535 can be seen illustrating a boundaryof RF propagation equal to a first threshold. Inside the first colorboundary 535, a second color boundary illustrating RF propagation at asecond threshold can be seen. In FIG. 10B the user has moved closer toaccess point 102 and has walked within the boundary of the first color535 such that directly in front of the user is the boundary of thesecond color 530. Above the user can be seen a portion of the firstboundary 535. The user is within a bubble defined by the first boundary535. FIG. 10C illustrates a further progression of the user's movementwithin the space where the user has turned to the left to illustratethat they are standing within the first boundary 535 and just outsidethe second boundary 530.

FIG. 11 illustrates another augmented reality embodiment. In FIG. 11user device 105 has captured an image of a space including an accesspoint 102 that is displayed by user device 105. Visualization service108 can display information about RF propagation surrounding the accesspoint in the displayed space. Additionally, user interface service 130can receive a selection 550 from a user tapping one of the access pointsdisplayed by device 105. The selection by the user of the access pointin the user interface can result in additional information about theaccess point being displayed.

FIG. 12 illustrates an example augmented reality embodiment wherein amenu 570 of details about an access point is displayed. The menu can bedisplayed as a result of receiving a selection of the access point suchas illustrated in FIG. 11 . Menu 570 can display information about theaccess point and can receive user inputs to change some parameters orconfigurations about the access point.

For example, menu 570 can display information such as access point name571, MAC address 572 of the access point, model information 573 for theaccess point, X, Y, and Z grid coordinate location of the access pointin the floor plan 574, the wireless protocols which access point isutilizing 575, antenna information 576, channel and transmission powerinformation 577.

Many of these fields are adjustable. For example, access point model 573can be changed. When the access point model is changed by the user asimulation of in RF propagation pattern for the new selected model canbe displayed. Such manipulation can be useful to see how a differentpiece of equipment might perform. Another useful change by the user canbe to change the channel of the access point 577. This can be usefulwhen interference is seen between two access points on the same channel.Changing the channel can remove the interference. When the channel ischanged visualization service 108 can display an updated visualizationshowing the effects of the channel change, and in some embodiments, auser can implement the channel change by pushing it to the access point.

Changing the antenna configuration 576 can be useful to change from a 2GHz to a 5 GHz antenna or vice-versa to increase range or communicationspeeds. Additionally, some antennas may provide directional benefits.These changes can be visualized by visualization service 108 in theaugmented reality display.

FIG. 13 shows an example of computing system 600, which can be forexample any computing device making up visualization system 100, or anycomponent thereof in which the components of the system are incommunication with each other using connection 605. Connection 605 canbe a physical connection via a bus, or a direct connection intoprocessor 610, such as in a chipset architecture. Connection 605 canalso be virtual, networked, or logical.

In some embodiments, computing system 600 is a distributed system inwhich the functions described in this disclosure can be distributedwithin a data center, multiple data centers, a peer network, etc. Insome embodiments, one or more of the described system componentsrepresents many such components each performing some or all of thefunction for which the component is described. In some embodiments, thecomponents can be physical or virtual devices.

Example system 600 includes at least one processing unit (CPU orprocessor) 610 and connection 605 that couples various system componentsincluding system memory 615, such as read-only memory (ROM) 620 andrandom access memory (RAM) 625 to processor 610. Computing system 600can include a cache of high-speed memory 612 connected directly with, inclose proximity to, or integrated as part of processor 610.

Processor 610 can include any general purpose processor and a hardwareservice or software service, such as services 632, 634, and 636 storedin storage device 630, configured to control processor 610 as well as aspecial-purpose processor where software instructions are incorporatedinto the actual processor design. Processor 610 may essentially be acompletely self-contained computing system, containing multiple cores orprocessors, a bus, memory controller, cache, etc. A multi-core processormay be symmetric or asymmetric.

To enable user interaction, computing system 600 includes an inputdevice 645, which can represent any number of input mechanisms, such asa microphone for speech, a touch-sensitive screen for gesture orgraphical input, keyboard, mouse, motion input, speech, etc. Computingsystem 600 can also include output device 635, which can be one or moreof a number of output mechanisms known to those of skill in the art. Insome instances, multimodal systems can enable a user to provide multipletypes of input/output to communicate with computing system 600.Computing system 600 can include communications interface 640, which cangenerally govern and manage the user input and system output. There isno restriction on operating on any particular hardware arrangement, andtherefore the basic features here may easily be substituted for improvedhardware or firmware arrangements as they are developed.

Storage device 630 can be a non-volatile memory device and can be a harddisk or other types of computer readable media which can store data thatare accessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs), read-only memory (ROM), and/or somecombination of these devices.

The storage device 630 can include software services, servers, services,etc., that when the code that defines such software is executed by theprocessor 610, it causes the system to perform a function. In someembodiments, a hardware service that performs a particular function caninclude the software component stored in a computer-readable medium inconnection with the necessary hardware components, such as processor610, connection 605, output device 635, etc., to carry out the function.

For clarity of explanation, in some instances, the present technologymay be presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

Any of the steps, operations, functions, or processes described hereinmay be performed or implemented by a combination of hardware andsoftware services or services, alone or in combination with otherdevices. In some embodiments, a service can be software that resides inmemory of a client device and/or one or more servers of a contentmanagement system and perform one or more functions when a processorexecutes the software associated with the service. In some embodiments,a service is a program or a collection of programs that carry out aspecific function. In some embodiments, a service can be considered aserver. The memory can be a non-transitory computer-readable medium.

In some embodiments, the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer-readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The executable computer instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, solid-state memory devices, flash memory, USB devices providedwith non-volatile memory, networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include servers,laptops, smartphones, small form factor personal computers, personaldigital assistants, and so on. The functionality described herein alsocan be embodied in peripherals or add-in cards. Such functionality canalso be implemented on a circuit board among different chips ordifferent processes executing in a single device, by way of furtherexample.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Aspect 1: A method of visualizing a W-Fi access point 3-D RF propagationpattern in Augmented Reality (AR), the method comprising: calculatingthe 3-D RF propagation pattern in a space for at least one Wi-Fi accesspoint based on a RF propagation model for the Wi-Fi access point;determining a location and orientation of a user device relative to theat least one Wi-Fi access point in the space; and presenting avisualization of the Wi-Fi access point RF propagation pattern overlaida first-person perspective view of the space based on the location andthe orientation of the user device relative to the at least one Wi-Fiaccess point.

Aspect 2: The method of Aspect 1, wherein the first-person perspectiveview of the space is an augmented reality view of the space, the methodcomprising: capturing at least one image of the space; displaying the atleast one image of the space on a display; and presenting thevisualization of the Wi-Fi access point RF propagation pattern on thedisplay overlaid the at least one image of the space.

Aspect 3: The method of any of Aspects 1 to 2, wherein the at least oneimage is a video made up of a plurality of images, the method furthercomprising: continuously determining the location and orientation of theuser device relative to the at least one Wi-Fi access point; anddynamically adjusting the visualization of the Wi-Fi access point RFpropagation pattern in coordination with the continuously determiningthe location and orientation of the user device relative to the at leastone Wi-Fi access point.

Aspect 4: The method of any of Aspects 1 to 3, wherein the dynamicallyadjusting the visualization of the Wi-Fi access point RF propagationpattern in coordination with the continuously determining the locationand orientation of the user device relative to the at least one Wi-Fiaccess point includes: representing the visualization of the Wi-Fiaccess point propagation in a first style at a first location of theuser device, and representing the visualization of the Wi-Fi accesspoint propagation in a second style at a second location of the userdevice.

Aspect 5: The method of any of Aspects 1 to 4, wherein the calculatingthe 3-D RF propagation pattern in a space for the at least one Wi-Fiaccess point based on a RF propagation model for the Wi-Fi access pointincludes: projecting a plurality of ray-paths in a plurality ofdirections in a 3-D space, where the ray-paths originate from the Wi-Fiaccess point and eminent in a variety of X, Y, and Z planes; determiningwhether the ray-paths interface with a building material defined in abuilding plan; for each ray-path of the ray-paths that interface with abuilding material, segmenting the respective ray-path into contiguoussegments of substantially uniform mediums; determining a RF signalstrength at points along the segments of the ray-paths, wherein thesignal degrades along the ray path as defined by the RF propagationmodel as a function of distance through the segment and characteristicsof RF propagation through the substantially uniform mediums throughwhich the segment traverses; 5. The method of any of Aspects 1 to 4,wherein the at least one image of the space includes an object that doesnot appear in the building plan, and the presenting the visualization ofthe Wi-Fi access point RF propagation pattern on the display overlaidthe at least one image of the space illustrates an aspect of Wi-Ficoverage in the area surrounding the object.

Aspect 6: The method of any of Aspects 1 to 5, wherein the at least oneimage of the space includes an object that does not appear in thebuilding plan, and the presenting the visualization of the Wi-Fi accesspoint RF propagation pattern on the display overlaid the at least oneimage of the space illustrates an aspect of Wi-Fi coverage in the areasurrounding the object.

Aspect 7: The method of any of Aspects 1 to 6, further comprising:detecting the object that does not appear in the building plan; andlabeling the object that does not appear in the building plan when anaspect of the Wi-Fi access point RF propagation pattern surrounding theobject is of poor quality as indicated by the aspect of the RFpropagation pattern being below a threshold.

Aspect 8: The method of any of Aspects 1 to 7, further comprising:identifying a portion of the building plan in the at least one image ofthe space; identifying a material that comprises the portion of thebuilding plan; determining that the material that comprises the portionof the building plan is different that the building material recordingthe building plan for the portion of the building plan; updating thebuilding plan with the identified material, whereby the calculating the3-D RF propagation pattern is updated using the updated building plan.

Aspect 9: The method of any of Aspects 1 to 8, further comprising:identifying a configuration change in the building plan from the atleast one image of the space; updating the building plan with theidentified material, whereby the calculating the 3-D RF propagationpattern is updated using the updated building plan.

Aspect 10: The method of any of Aspects 1 to 9, wherein the determiningthe location and the orientation of the user device relative to the atleast one Wi-Fi access point in the space comprises: detecting at leastone indicator on the Wi-Fi access point that uniquely identifies theWi-Fi access point and/or the location of the Wi-Fi access pint.

Aspect 11: The method of any of Aspects 1 to 10, further comprising:after detecting the at least one indicator on the Wi-Fi access point,communicating with a database to learn an identification of the Wi-Fiaccess point, its location and/or its orientation in the space.

Aspect 12: The method of any of Aspects 1 to 11, wherein the at leastone indicator is a QR code, symbols, an optical pattern, a pattern ofblinking lights, or the orientation and geometry of a housing of theWi-Fi access point.

Aspect 13: The method of any of Aspects 1 to 12, wherein the determiningthe location and the orientation of the user device relative to the atleast one Wi-Fi access point in the space comprises: detecting at leastone indicator on the Wi-Fi access point that indicates an orientation ofthe Wi-Fi access point in the space.

Aspect 14: The method of any of Aspects 1 to 13, wherein the at leastone indicator on the Wi-Fi access point that indicates an orientation ofthe Wi-Fi access point is the physical shape of the Wi-Fi access point.

Aspect 15: The method of any of Aspects 1 to 14, wherein thevisualization of the Wi-Fi access point RF propagation patternillustrates at least one attribute of the Wi-Fi propagation pattern,such as signal-to-noise ratio (SNR), signal strength, interference,channel, etc.

Aspect 16: The method of any of Aspects 1 to 15, further comprising:receiving a selection of the Wi-Fi access point in the visualization;after the selection, presenting statistics and information pertaining tothe Wi-Fi access point.

Aspect 17: The method of any of Aspects 1 to 16, further comprising:receiving a selection of the Wi-Fi access point in the visualization;after the selection, presenting options pertaining to additionalvisualizations the Wi-Fi access point RF propagation pattern; and afterreceiving a selection of an option from the option, presenting avisualization the Wi-Fi access point RF propagation patterncorresponding to the selected option.

Aspect 18: The method of any of Aspects 1 to 17, further comprising:labeling a reference icon indicating a first Wi-Fi access point in thespace through which the user device is presently communicating [thefirst Wi-Fi access point could be different that the at least one accesspoint for which you are viewing the RF propagation pattern].

Aspect 19: The method of any of Aspects 1 to 18, wherein the at leastone Wi-Fi access is a plurality of Wi-Fi access points, and thevisualization of the Wi-Fi access point RF propagation patternillustrates RF propagation patterns for the plurality of Wi-Fi accesspoints.

What is claimed is:
 1. A method comprising: projecting a plurality ofray-paths in a plurality of directions in a 3-dimensional space;determining whether the plurality of ray-paths interface with a buildingmaterial; for each ray-path of the plurality of ray-paths that interfacewith the building material, segmenting the respective ray-path intocontiguous segments of substantially uniform mediums; and determiningradio frequency (RF) signal strengths at points along the contiguoussegments.
 2. The method of claim 1, where the RF signal strengthdegrades along the contiguous segments as defined by an RF propagationmodel as a function of distance through the contiguous segments andcharacteristics of RF propagation through the substantially uniformmediums.
 3. The method of claim 1, wherein the plurality of ray pathsoriginate from one or more access points and emanate in a variety of X,Y and Z planes.
 4. The method of claim 1, further comprising: receivinginformation related to the ray-paths that interface with the buildingmaterial at a virtualization service; and determining, at thevirtualization service, RF signal strength at particular points alongthe contiguous segments using the information and an RF propagationmodel.
 5. The method of claim 1, wherein the RF signal strength isvisualized in augmented reality.
 6. The method of claim 1, furthercomprising: receiving location and orientation information of a userdevice relative to at least one access point in which one or moreray-paths of the plurality of ray-paths are originated; displaying, on adisplay of the user device, a camera view; and overlaying avisualization of the RF signal strength on the camera view utilizing thelocation and orientation information.
 7. The method of claim 6, whereinthe visualization of the RF signal strength is dome shaped.
 8. A systemcomprising: at least one processor; and at least one memory storinginstructions, which when executed by the at least one processor, causesthe at least one processor to: project a plurality of ray-paths in aplurality of directions in a 3-dimensional space; determine whether theplurality of ray-paths interface with a building material; for eachray-path of the plurality of ray-paths that interface with the buildingmaterial, segment the respective ray-path into contiguous segments ofsubstantially uniform mediums; and determine radio frequency (RF) signalstrengths at points along the contiguous segments.
 9. The system ofclaim 8, where the RF signal strength degrades along the contiguoussegments as defined by an RF propagation model as a function of distancethrough the contiguous segments and characteristics of RF propagationthrough the substantially uniform mediums.
 10. The system of claim 8,wherein the plurality of ray paths originate from one or more accesspoints and emanate in a variety of X, Y and Z planes.
 11. The system ofclaim 8, further comprising instructions, which when executed by the atleast one processor, causes the at least one processor to: receiveinformation related to the ray-paths that interface with the buildingmaterial at a virtualization service; and determine, at thevirtualization service, RF signal strength at particular points alongthe contiguous segments using the information and an RF propagationmodel.
 12. The system of claim 8, wherein the RF signal strength isvisualized in augmented reality.
 13. The system of claim 8, furthercomprising instructions, which when executed by the at least oneprocessor, causes the at least one processor to: receive location andorientation information of a user device relative to at least one accesspoint in which one or more ray-paths of the plurality of ray-paths areoriginated; display, on a display of the user device, a camera view; andoverlay a visualization of the RF signal strength on the camera viewutilizing the location and orientation information.
 14. The system ofclaim 13, wherein the visualization of the RF signal strength is domeshaped.
 15. At least one non-transitory computer-readable medium storinginstructions, which when executed by at least one processor, causes theat least one processor to: project a plurality of ray-paths in aplurality of directions in a 3-dimensional space; determine whether theplurality of ray-paths interface with a building material; for eachray-path of the plurality of ray-paths that interface with the buildingmaterial, segment the respective ray-path into contiguous segments ofsubstantially uniform mediums; and determine radio frequency (RF) signalstrengths at points along the contiguous segments.
 16. The at least onenon-transitory computer-readable medium of claim 15, where the RF signalstrength degrades along the contiguous segments as defined by an RFpropagation model as a function of distance through the contiguoussegments and characteristics of RF propagation through the substantiallyuniform mediums.
 17. The at least one non-transitory computer-readablemedium of claim 15, wherein the plurality of ray paths originate fromone or more access points and emanate in a variety of X, Y and Z planes.18. The at least one non-transitory computer-readable medium of claim15, further comprising instructions, which when executed by the at leastone processor, causes the at least one processor to: receive informationrelated to the ray-paths that interface with the building material at avirtualization service; and determine, at the virtualization service, RFsignal strength at particular points along the contiguous segments usingthe information and an RF propagation model.
 19. The at least onenon-transitory computer-readable medium of claim 15, wherein the RFsignal strength is visualized in augmented reality.
 20. The at least onenon-transitory computer-readable medium of claim 15, further comprisinginstructions, which when executed by the at least one processor, causesthe at least one processor to: receive location and orientationinformation of a user device relative to at least one access point inwhich one or more ray-paths of the plurality of ray-paths areoriginated; display, on a display of the user device, a camera view; andoverlay a visualization of the RF signal strength on the camera viewutilizing the location and orientation information.